Activity Recognition

Human Activity Recognition is the problem of identifying events performed by humans given a video input. It is formulated as a binary (or multiclass) classification problem of outputting activity class labels. Activity Recognition is an important problem with many societal applications including smart surveillance, video search/retrieval, intelligent robots, and other monitoring systems.

Source: Learning Latent Sub-events in Activity Videos Using Temporal Attention Filters

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 751–760 of 1322 papers

Title	Date	Tasks	Status
WATCH: Wasserstein Change Point Detection for High-Dimensional Time Series Data	Jan 18, 2022	Activity RecognitionChange Point Detection	—Unverified
Weakly Supervised Multi-Task Representation Learning for Human Activity Analysis Using Wearables	Aug 6, 2023	Activity RecognitionHuman Activity Recognition	—Unverified
Weakly Supervised Temporal Convolutional Networks for Fine-grained Surgical Activity Recognition	Feb 21, 2023	Activity Recognition	—Unverified
Wearable Accelerometer Foundation Models for Health via Knowledge Distillation	Dec 15, 2024	Activity Recognitioncross-modal alignment	—Unverified
Wearable-based behaviour interpolation for semi-supervised human activity recognition	May 24, 2024	Activity RecognitionDeep Learning	—Unverified
Wearable Sensor Data Based Human Activity Recognition using Machine Learning: A new approach	May 9, 2019	Activity RecognitionBIG-bench Machine Learning	—Unverified
When Vehicles See Pedestrians with Phones:A Multi-Cue Framework for Recognizing Phone-based Activities of Pedestrians	Jan 24, 2018	Activity RecognitionDecision Making	—Unverified
Who did What at Where and When: Simultaneous Multi-Person Tracking and Activity Recognition	Jul 3, 2018	Activity RecognitionVisual Tracking	—Unverified
WiFi-based Spatiotemporal Human Action Perception	Jun 20, 2022	Activity RecognitionHuman Activity Recognition	—Unverified
Wi-Fringe: Leveraging Text Semantics in WiFi CSI-Based Device-Free Named Gesture Recognition	Aug 16, 2019	Activity RecognitionGesture Recognition	—Unverified

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All datasets RWF-2000 Stanford40 First-Person Hand Action Benchmark Self-stimulatory Behavior Dataset

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	Structured Keypoint Pooling	Accuracy	93.4	—	Unverified
2	Semi-Supervised Hard Attention (SSHA); pretrained on Deepmind Kinetics dataset	Accuracy	90.4	—	Unverified
3	Human Skeletons + Change Detection	Accuracy	90.25	—	Unverified
4	Separable Convolutional LSTM	Accuracy	89.75	—	Unverified
5	SPIL Convolution	Accuracy	89.3	—	Unverified
6	Flow Gated Network	Accuracy	87.25	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FocusCLIP	Top-3 Accuracy (%)	10.47	—	Unverified
2	CLIP	Top-3 Accuracy (%)	6.49	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Boutaleb et al.	1:1 Accuracy	97.91	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	all-landmark-model	Activity Recognition	0.76	—	Unverified